SOTAVerified

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2001–2025 of 6748 papers

TitleStatusHype
Behave-XAI: Deep Explainable Learning of Behavioral Representational Data—0
Differential Recurrent Neural Networks for Action Recognition—0
Dynamic Hurst Exponent in Time Series—0
Stochastically forced ensemble dynamic mode decomposition for forecasting and analysis of near-periodic systems—0
Comparison of end-to-end neural network architectures and data augmentation methods for automatic infant motility assessment using wearable sensors—0
Comparison of Different Methods for Time Sequence Prediction in Autonomous Vehicles—0
A Review of Intelligent Practices for Irrigation Prediction—0
Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy—0
Digital biomarkers and artificial intelligence for mass diagnosis of atrial fibrillation in a population sample at risk of sleep disordered breathing—0
Digital Twin Framework for Time to Failure Forecasting of Wind Turbine Gearbox: A Concept—0
Benchmarking adversarial attacks and defenses for time-series data—0
A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals—0
Super-resolution of Time-series Labels for Bootstrapped Event Detection—0
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization—0
Comparison between DeepESNs and gated RNNs on multivariate time-series prediction—0
Comparison Analysis of Facebook's Prophet, Amazon's DeepAR+ and CNN-QR Algorithms for Successful Real-World Sales Forecasting—0
Dimension Reduction for time series with Variational AutoEncoders—0
Direct detection of pixel-level myocardial infarction areas via a deep-learning algorithm—0
Direct Estimation of Pharmacokinetic Parameters from DCE-MRI using Deep CNN with Forward Physical Model Loss—0
Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning—0
Direct Mapping Hidden Excited State Interaction Patterns from ab initio Dynamics and Its Implications on Force Field Development—0
Direct Method for Training Feed-forward Neural Networks using Batch Extended Kalman Filter for Multi-Step-Ahead Predictions—0
Direct Signal Separation Via Extraction of Local Frequencies with Adaptive Time-Varying Parameters—0
Discovering Causal Relations in Textual Instructions—0
Comparing Time-Series Analysis Approaches Utilized in Research Papers to Forecast COVID-19 Cases in Africa: A Literature Review—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified